A metabolomic approach to determine the geographical origins of Anemarrhena asphodeloides by using UPLC-QTOF MS

Nahyun Kim; Seung Mok Ryu; Dong Hyuk Lee; Jae Won Lee; Eun Kyoung Seo; Je Hyun Lee; Dongho Lee

doi:10.1016/j.jpba.2013.12.040

A metabolomic approach to determine the geographical origins of Anemarrhena asphodeloides by using UPLC-QTOF MS

Nahyun Kim, Seung Mok Ryu, Dong Hyuk Lee, Jae Won Lee, Eun Kyoung Seo, Je Hyun Lee, Dongho Lee

Department of Pharmaceutical Sciences

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

An ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS) method was developed for metabolite profiling of Anemarrhena asphodeloides Bunge from two different geographical origins. In this study, the metabolite profile data obtained using UPLC-QTOF MS was subjected to multivariate statistical analyses, such as the principal component analysis and the hierarchical clustering analysis, to compare metabolite patterns among A. asphodeloides samples. Furthermore, a metabolite selection method known as significance analysis of microarrays (SAM) was applied to further select metabolites and to identify key constituents to efficiently distinguish between geographical origins. The UPLC-QTOF MS analysis successfully classified 21 samples into two distinct groups according to their geographical origins. The validation method used to assess the analytical stability and accuracy of these data is also described. These results suggest that this proposed method is reliable, accurate, and effective for geographic classification of A. asphodeloides, thus guiding its proper use for therapeutic purposes.

Original language	English
Pages (from-to)	47-52
Number of pages	6
Journal	Journal of Pharmaceutical and Biomedical Analysis
Volume	92
DOIs	https://doi.org/10.1016/j.jpba.2013.12.040
State	Published - 15 Apr 2014

Bibliographical note

Funding Information:
This work was supported by a grant from the Korea Food and Drug Administration for Studies on Standardization of Herbal Medicine (2008) and a Korea University Grant .

Keywords

Anemarrhena asphodeloides
Metabolite profiling
Metabolite selection
Method validation
UPLC-QTOF MS

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10.1016/j.jpba.2013.12.040

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@article{882c2a59b1754159a166fa1d62841e7a,

title = "A metabolomic approach to determine the geographical origins of Anemarrhena asphodeloides by using UPLC-QTOF MS",

abstract = "An ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS) method was developed for metabolite profiling of Anemarrhena asphodeloides Bunge from two different geographical origins. In this study, the metabolite profile data obtained using UPLC-QTOF MS was subjected to multivariate statistical analyses, such as the principal component analysis and the hierarchical clustering analysis, to compare metabolite patterns among A. asphodeloides samples. Furthermore, a metabolite selection method known as significance analysis of microarrays (SAM) was applied to further select metabolites and to identify key constituents to efficiently distinguish between geographical origins. The UPLC-QTOF MS analysis successfully classified 21 samples into two distinct groups according to their geographical origins. The validation method used to assess the analytical stability and accuracy of these data is also described. These results suggest that this proposed method is reliable, accurate, and effective for geographic classification of A. asphodeloides, thus guiding its proper use for therapeutic purposes.",

keywords = "Anemarrhena asphodeloides, Metabolite profiling, Metabolite selection, Method validation, UPLC-QTOF MS",

author = "Nahyun Kim and Ryu, {Seung Mok} and Lee, {Dong Hyuk} and Lee, {Jae Won} and Seo, {Eun Kyoung} and Lee, {Je Hyun} and Dongho Lee",

note = "Funding Information: This work was supported by a grant from the Korea Food and Drug Administration for Studies on Standardization of Herbal Medicine (2008) and a Korea University Grant . ",

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doi = "10.1016/j.jpba.2013.12.040",

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AU - Kim, Nahyun

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AU - Lee, Dong Hyuk

AU - Lee, Jae Won

AU - Seo, Eun Kyoung

AU - Lee, Je Hyun

AU - Lee, Dongho

N1 - Funding Information: This work was supported by a grant from the Korea Food and Drug Administration for Studies on Standardization of Herbal Medicine (2008) and a Korea University Grant .

PY - 2014/4/15

Y1 - 2014/4/15

N2 - An ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS) method was developed for metabolite profiling of Anemarrhena asphodeloides Bunge from two different geographical origins. In this study, the metabolite profile data obtained using UPLC-QTOF MS was subjected to multivariate statistical analyses, such as the principal component analysis and the hierarchical clustering analysis, to compare metabolite patterns among A. asphodeloides samples. Furthermore, a metabolite selection method known as significance analysis of microarrays (SAM) was applied to further select metabolites and to identify key constituents to efficiently distinguish between geographical origins. The UPLC-QTOF MS analysis successfully classified 21 samples into two distinct groups according to their geographical origins. The validation method used to assess the analytical stability and accuracy of these data is also described. These results suggest that this proposed method is reliable, accurate, and effective for geographic classification of A. asphodeloides, thus guiding its proper use for therapeutic purposes.

AB - An ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS) method was developed for metabolite profiling of Anemarrhena asphodeloides Bunge from two different geographical origins. In this study, the metabolite profile data obtained using UPLC-QTOF MS was subjected to multivariate statistical analyses, such as the principal component analysis and the hierarchical clustering analysis, to compare metabolite patterns among A. asphodeloides samples. Furthermore, a metabolite selection method known as significance analysis of microarrays (SAM) was applied to further select metabolites and to identify key constituents to efficiently distinguish between geographical origins. The UPLC-QTOF MS analysis successfully classified 21 samples into two distinct groups according to their geographical origins. The validation method used to assess the analytical stability and accuracy of these data is also described. These results suggest that this proposed method is reliable, accurate, and effective for geographic classification of A. asphodeloides, thus guiding its proper use for therapeutic purposes.

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A metabolomic approach to determine the geographical origins of Anemarrhena asphodeloides by using UPLC-QTOF MS

Abstract

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Keywords

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